Recent interesting robotics papers
Visuomotor Policies to Grasp Anything with Dexterous Hands

- grasping based on stero input
- engineering example of teacher-student, sim2real, and geometric fabrics

#arxiv #dexterous #grasp #sim2real

X Overview, Project Website, Geometric Fabrics
🧵 Thread • FixupX
Ritvik Singh (@ritvik_singh9)
Excited to announce our latest work: DextrAH-RGB where we successfully train visuomotor policies in sim to perform dexterous grasping of arbitrary objects end-to-end from RGB input!
arxiv dexterous grasp sim2real
GraspVLA: a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data

- combination of sim and real could help train robust grasping policy
- engineering example of pi-0 policy (VLM + flow matching)

#arxiv #grasp #simulation #sim2real #flow_matching

X Overview, Project Website, NVidia GraspGen
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Tuo Liu (@TuoLiuRobot)
Tuo Liu (@TuoLiuRobot)
Galbot（银河通用）has just dropped GraspVLA, the world’s first end-to-end embodied grasping model! Trained on over a billion “visual-language-action” pairs, GraspVLA is ready to handle a wide range of tasks, even the unexpected ones.

And with a little post-training…
arxiv grasp simulation sim2real flow_matching
Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning

- efficient RL algorithm to improve rollout performance

#ICLR2025 #RL #sim2real #refinement

X Overview, Project Website
🧵 Thread • FixupX
Patrick Yin (@patrickhyin)
Current RL finetuning methods are too inefficient to make autonomous real world robot learning tractable. We propose Simulation-Guided Fine-Tuning (SGFT) - a simple, general sim2real framework that extracts structured exploration priors from sim to accelerate…
ICLR2025 RL sim2real refinement
 
 
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